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Evaluating Data Handling Performance of ISSEI Data Management Method

机译:评估ISSEI数据管理方法的数据处理性能

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A new data management method called "ISSEI" was proposed in the previous report [1], to avoid slowing down of data retrieving time for the database that has an inherent nature of ever growing data volume. The experimental evaluation showed that ISSEI had a significantly faster data retrieving time and required less CPU and RAM usages in the database server. This paper deals with additional evaluations of other data handling performances as the necessary steps towards a successful replacement of the conventional commercial DBMS by ISSEI. Experimental comparisons between MS SQL Server and ISSEI were conducted by changing the size of data volumes in the database, having revealed interesting results. One interesting result is that ISSEI shows faster updating and deleting time in large data volume sizes than MS SQL Server, but slower adding time in any data volume size than the MS SQL Server. Another interesting observed result is that while the MS SQL Server's performance depends on the size of the data volume to be handled at a time, ISSEI's performance shows no dependency on the data volume size. These two additional evaluation results are showing that the proposed ISSEI data management method has superiority in massive data handling over the conventional commercial DBMS.
机译:在先前的报告中[1]提出了一种称为“ ISSEI”的新数据管理方法,以避免因具有不断增长的数据量的固有特性而减慢数据库的数据检索时间。实验评估表明,ISSEI的数据检索时间明显更快,并且数据库服务器中的CPU和RAM使用量更少。本文将对其他数据处理性能进行额外评估,以此作为ISSEI成功替代传统商业DBMS的必要步骤。通过更改数据库中数据量的大小,进行了MS SQL Server和ISSEI之间的实验比较,发现了有趣的结果。一个有趣的结果是,与MS SQL Server相比,ISSEI在大数据量大小中显示更快的更新和删除时间,但是在任何数据量大小中都比MS SQL Server显示更新和删除时间慢。观察到的另一个有趣结果是,尽管MS SQL Server的性能取决于一次要处理的数据量的大小,但是ISSEI的性能却不依赖于数据量的大小。这两个额外的评估结果表明,与传统的商用DBMS相比,所提出的ISSEI数据管理方法在海量数据处理方面具有优势。

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